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Real-time conditional forecasts with Bayesian VARs: An application to New Zealand

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  • Bloor, Chris
  • Matheson, Troy

Abstract

Abstract We develop a Bayesian VAR (BVAR) to produce conditional forecasts for the New Zealand economy. In a real-time out-of-sample forecasting exercise, we find that the BVAR outperforms a selection of other time series models, and it yields forecasts of similar accuracy to the forecasts produced internally at the Reserve Bank of New Zealand. Examining shock decompositions, we also highlight the importance of foreign shocks for the New Zealand economy. Our results suggest that the BVAR is a useful tool for policy making in real time.

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Bibliographic Info

Article provided by Elsevier in its journal The North American Journal of Economics and Finance.

Volume (Year): 22 (2011)
Issue (Month): 1 (January)
Pages: 26-42

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Handle: RePEc:eee:ecofin:v:22:y:2011:i:1:p:26-42

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Web page: http://www.elsevier.com/locate/inca/620163

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Keywords: Bayesian VAR Conditional forecasts Real time;

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References

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  1. Troy Matheson, 2007. "An analysis of the informational content of New Zealand data releases: the importance of business opinion surveys," Reserve Bank of New Zealand Discussion Paper Series DP2007/13, Reserve Bank of New Zealand.
  2. Daniel F. Waggoner & Tao Zha, 1998. "Conditional forecasts in dynamic multivariate models," Working Paper 98-22, Federal Reserve Bank of Atlanta.
  3. Christopher A. Sims, 1992. "A Nine Variable Probabilistic Macroeconomic Forecasting Model," Cowles Foundation Discussion Papers 1034, Cowles Foundation for Research in Economics, Yale University.
  4. Matheson, Troy, 2010. "Assessing the fit of small open economy DSGEs," Journal of Macroeconomics, Elsevier, vol. 32(3), pages 906-920, September.
  5. De Mol, Christine & Giannone, Domenico & Reichlin, Lucrezia, 2008. "Forecasting using a large number of predictors: Is Bayesian shrinkage a valid alternative to principal components?," Journal of Econometrics, Elsevier, vol. 146(2), pages 318-328, October.
  6. Troy Matheson, 2005. "Factor model forecasts for New Zealand," Reserve Bank of New Zealand Discussion Paper Series DP2005/01, Reserve Bank of New Zealand.
  7. Lawrence J. Christiano & Martin Eichenbaum & Charles L. Evans, 1997. "Monetary policy shocks: what have we learned and to what end?," Working Paper Series, Macroeconomic Issues WP-97-18, Federal Reserve Bank of Chicago.
  8. Chris Bloor & Troy Matheson, 2008. "Analysing shock transmission in a data-rich environment: A large BVAR for New Zealand," Reserve Bank of New Zealand Discussion Paper Series DP2008/09, Reserve Bank of New Zealand.
  9. Clarida, Richard & Galí, Jordi & Gertler, Mark, 1999. "The Science of Monetary Policy: A New Keynesian Perspective," CEPR Discussion Papers 2139, C.E.P.R. Discussion Papers.
  10. David O. Cushman & Tao Zha, 1995. "Identifying monetary policy in a small open economy under flexible exchange rates," Working Paper 95-7, Federal Reserve Bank of Atlanta.
  11. Marco Del Negro & Frank Schorfheide, 2002. "Priors from general equilibrium models for VARs," Working Paper 2002-14, Federal Reserve Bank of Atlanta.
  12. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-44, January.
  13. Waggoner, Daniel F. & Zha, Tao, 2003. "A Gibbs sampler for structural vector autoregressions," Journal of Economic Dynamics and Control, Elsevier, vol. 28(2), pages 349-366, November.
  14. Thomas Doan & Robert B. Litterman & Christopher A. Sims, 1986. "Forecasting and conditional projection using realistic prior distribution," Staff Report 93, Federal Reserve Bank of Minneapolis.
  15. Kadiyala, K. Rao & Karlsson, Sune, 1994. "Numerical Aspects of Bayesian VAR-modeling," Working Paper Series in Economics and Finance 12, Stockholm School of Economics.
  16. John C. Robertson & Ellis W. Tallman, 1999. "Vector autoregressions: forecasting and reality," Economic Review, Federal Reserve Bank of Atlanta, issue Q1, pages 4-18.
  17. Zha, Tao, 1999. "Block recursion and structural vector autoregressions," Journal of Econometrics, Elsevier, vol. 90(2), pages 291-316, June.
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Citations

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Cited by:
  1. Henzel, Steffen R. & Mayr, Johannes, 2013. "The mechanics of VAR forecast pooling—A DSGE model based Monte Carlo study," The North American Journal of Economics and Finance, Elsevier, vol. 24(C), pages 1-24.
  2. Domenico Giannone & Michèle Lenza & Giorgio E. Primiceri, 2012. "Prior Selection for Vector Autoregressions," Working Papers ECARES ECARES 2012-002, ULB -- Universite Libre de Bruxelles.
  3. Chris McDonald & Leif Anders Thorsrud, 2011. "Evaluating density forecasts: model combination strategies versus the RBNZ," Reserve Bank of New Zealand Discussion Paper Series DP2011/03, Reserve Bank of New Zealand.
  4. Kurmas Akdogan & Selen Baser & Meltem Gulenay Chadwick & Dilara Ertug & Timur Hulagu & Sevim Kosem & Fethi Ogunc & M. Utku Ozmen & Necati Tekatli, 2012. "Short-Term Inflation Forecasting Models For Turkey and a Forecast Combination Analysis," Working Papers 1209, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
  5. Auer, Simone, 2014. "Monetary policy shocks and foreign investment income: evidence from a large Bayesian VAR," Globalization and Monetary Policy Institute Working Paper 170, Federal Reserve Bank of Dallas.
  6. Chris McDonald, 2012. "Kiwi drivers the New Zealand dollar experience," Reserve Bank of New Zealand Analytical Notes series AN2012/02, Reserve Bank of New Zealand.
  7. Karlsson, Sune, 2012. "Forecasting with Bayesian Vector Autoregressions," Working Papers 2012:12, Örebro University, School of Business.
  8. Chris Bloor, 2009. "The use of statistical forecasting models at the Reserve Bank of New Zealand," Reserve Bank of New Zealand Bulletin, Reserve Bank of New Zealand, vol. 72, pages 21-26, June.

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